4.6 Article

Epithelial to mesenchymal transition predicts gefitinib resistance in cell lines of head and neck squamous cell carcinoma and non-small cell lung carcinoma

Journal

MOLECULAR CANCER THERAPEUTICS
Volume 6, Issue 6, Pages 1683-1691

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1535-7163.MCT-07-0138

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Funding

  1. NCI NIH HHS [P50 CA058187, P30 CA046934] Funding Source: Medline

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The modest response of patients with head and neck squamous cell carcinoma (HNSCC) and non-small cell lung carcinoma (NSCLC) to epithelial growth factor receptor tyrosine kinase inhibitors such as gefitinib and erlotinib indicates the need for the development of biomarkers to predict response. We determined gefitinib sensitivity in a panel of HNSCC cell lines by a 5-day 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and confirmed these responses with analysis of downstream signaling by immunoblotting and cell cycle arrest. Basal gene expression profiles were then determined by microarray analysis and correlated with gefitinib response. These data were combined with previously reported NSCLC microarray results to generate a broader predictive index. Common markers of resistance between the two tumor types included genes associated with the epithelial to mesenchymal transition. We confirmed that increased protein expression of vimentin combined with the loss of E-cadherin, claudin 4, and claudin 7 by immunoblotting was associated with gefitinib resistance in both HNSCC and NSCLC cell lines. In addition, the loss of the Ca2+-independent cell-cell adhesion molecules EpCAM and TROP2 in resistant lines was confirmed by immunofluorescence. Tumor xenografts derived from the gefitinibsensitive UM-SCC-2 were growth-delayed by gefitinib, whereas the gefitinib-resistant 1483 xenografts were unaffected. These data support a role for epithelial to mesenchymal transition in establishing gefitinib resistance for both HNSCC and NSCLC, and indicate that clinical trials should address whether these biomarkers will be useful for patient selection.

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